Retail stores, such as grocery stores and other types of stores, offer a number of products, services, and items for purchase by customers. Typically, a customer will choose which items he or she wishes to purchase, and proceed to a point of sale system (POS) where an associate or employee of the retail store (e.g., a cashier), or self-checkout system, will facilitate a checkout for the chosen items. Although many items include codes on their packaging (e.g., UPCs or other barcodes) that may be read or detected by a scanner, many other items, including unpackaged items, do not include codes that may be read or detected. In a grocery store, for example, produce and fresh bakery items include an associated a price look-up (PLU) code that must be manually input into a POS system.
Although some items may have the PLU affixed thereon, many items are absent a PLU, and the cashier is therefore responsible for identifying the correct PLU for an item and inputting the PLU into the POS system. However, it is difficult to memorize the numerous PLUs for the numerous items offered for sale by a retail store, and errors and inefficiencies may result. Additionally, retail stores typically face high turnover rates for cashiers, and training new cashiers on PLU codes is expensive and time-consuming.
Accordingly, there is an opportunity to implement speech recognition technologies in POS systems to enable retail store individuals (e.g., cashiers) to effectively and efficiently handle item checkouts in retail stores, especially high-volume and high-frequency checkouts that often include many unpackaged items.